Error while applying your model about air-asvspoof HOT 13 CLOSED

Thank you for your question. Could you please let me know the shape of the input feature you feed into the model? I am not sure if you preprocess the raw audio properly.

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In this repo, we provided the MATLAB code for preprocessing. If you prefer to use Python, please refer to preprocess.py in our new repo for the recent work https://github.com/yzyouzhang/Empirical-Channel-CM. Thanks.

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torch.Size([60, 750])

Please find my notebook file what i am doing.

How can i connect with you? email id?
notebook_air_2.zip

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@yzyouzhang Also i am not able to train the model from scratch , it give me error:
Batch size = 2
GPU : RTX 2060 6 GB

RuntimeError: CUDA out of memory. Tried to allocate 60.00 MiB (GPU 0; 6.00 GiB total capacity; 4.49 GiB already allocated; 0 bytes free; 4.52 GiB reserved in total by PyTorch)

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torch.Size([60, 750])

Please find my notebook file what i am doing.

How can i connect with you? email id? notebook_air_2.zip

The feature size should be [B, 1, 60, 750].
I checked your code. You have ResNet(1, 16) when you set up the model. It should be ResNet(3, 256) if you want to use my pretrained model.

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@yzyouzhang Also i am not able to train the model from scratch , it give me error: Batch size = 2 GPU : RTX 2060 6 GB

RuntimeError: CUDA out of memory. Tried to allocate 60.00 MiB (GPU 0; 6.00 GiB total capacity; 4.49 GiB already allocated; 0 bytes free; 4.52 GiB reserved in total by PyTorch)

In my case, I use RTX 1080 Ti 11GB. I can load with batch size 64. So I think batch size 2 should be totally OK for your device. Have you made sure there are no other processes occupying the GPU memory?

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@yzyouzhang how can i convert my feature size (60,750) to [B, 1, 60, 750].

what is B and 1 means?

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@yzyouzhang i checked it again , no other process occupying my gpu memory.

could you please share your id or zoom id for further contact to solve this issue?

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@yzyouzhang what threshold score you have set for real and fake samples?
score = F.softmax(lfcc_outputs)[:, 0]
score

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@yzyouzhang how can i convert my feature size (60,750) to [B, 1, 60, 750].

what is B and 1 means?

B is the batch size, 1 is the number of channels for CNN.

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@yzyouzhang what threshold score you have set for real and fake samples? score = F.softmax(lfcc_outputs)[:, 0] score

We do not need a threshold to calculate EER. If you want to classify samples into two classes, you can choose a value between the r1 and r2 of the OCSoftmax.

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@yzyouzhang i checked it again , no other process occupying my gpu memory.

could you please share your id or zoom id for further contact to solve this issue?

Please contact [email protected] for further zoom discussions. Thanks.

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ok thanks :)

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